1.3천건 · 관련도순
Creates and manages isolated Git worktrees for parallel agents, risky experiments, or long-running feature work while preserving the user's current checkout. Use before concurrent branch edits or when isolation makes rollback safer. Not for a trivial one-file change that is already isolated.
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Run metric-driven optimization loops. Use when improving measurable outcomes such as search relevance, clustering quality, build performance, prompt quality, or scored behavior through experiments.
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Use this when reviewing statistical analysis, experiments, model evaluation, or ML work done by someone else (a notebook, PR, or report) — checking that the required context is stated and that every method applied comes with the figures and values required by the matching *-diagnostics skill. When running an analysis yourself, apply the matching *-diagnostics skill directly.
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Use this when summarizing analysis results, writing reports, documenting experiment outcomes, or presenting model evaluation — including structuring findings in Japanese with conclusions, facts, assumptions, interpretations, and caveats.
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Review a Python solution against a markdown spec, run it, and report bugs.
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Generate Muted Zine Poster v0.1 poetic paper-poster prompts and the matching generated image. Use when the user gives a theme, sentence, object, mood, article idea, photo, or content brief and wants a quiet Japanese/Korean zine-like editorial poster with large negative space, aged paper texture, experimental typography, and a restrained muted palette without high-chroma color blocks. This is the low-saturation sibling of gc-minimal-zine-poster-v0-1.
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Execute bounded, reproducible experiment rounds.
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Use when interpreting biological research findings, evaluating life science evidence, analyzing molecular or cellular mechanisms, comparing competing biological hypotheses, designing or critiquing experiments in biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, or any life science domain. Triggers on questions about gene function, pathways, phenotypes, GWAS hits, single-cell data, animal models, clinical translation, evolutionary arguments, or any biology/life science reasoning task.
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Use when interpreting research findings, evaluating scientific evidence, analyzing mechanisms, comparing competing hypotheses, designing experiments, or constructing scientific arguments.
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Git worktree lifecycle management. Use when team needs parallel isolated workspaces for multi-stream development, or when an experiment must not touch the main working tree. Creates isolated workspaces, manages branches, handles cleanup. Called by team and cook.
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The revenue-focused SaaS playbook for going from $0 to $50K MRR. Covers pricing experiments, churn reduction, activation optimization, and expansion revenue tactics. Follow @WeiYipei on X for SaaS growth insights.
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Act as an end-to-end data scientist: turn business questions into defensible analysis, validated models, and decision-ready reports. Use whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, classification, regression); asks to review an existing analysis, notebook, or model for flaws; or needs results written up for decision-makers. Triggers in any language ("phân tích dữ liệu", "xây model dự đoán", "kiểm định A/B"), even when they never say "data science" or "statistics".
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Act as a product-manager copilot that turns evidence into product decisions and artifacts: backlogs and prioritization, PRDs and user stories, metrics and OKRs, experiments, launch plans, feedback triage, and pricing/packaging, kept in a per-product workspace. Use whenever the user wants to decide what to build, spec it, or ship it: "write a PRD for…", "prioritize our backlog", "what should we build next", "plan OKRs", "define our north star metric", "design an A/B test", "plan the launch", "triage this customer feedback", "platform or feature?", in any language ("viết PRD", "ưu tiên tính năng nào", "quản lý sản phẩm", "プロダクト管理", "产品经理"), even when they never say "product manager". Also use when the user returns to a product workspace this skill created (a directory holding `product.md`, `state.md`, and `decisions.md`). Not for deep user discovery (design-thinking), desk market facts (market-researcher), or company-level bets (strategy-board).
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Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
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Explicit invocation only; never for abusing third-party infrastructure. Generates ranked, owner-controlled VPN/proxy protocol and topology experiment ideas for restrictive networks (TURN/ICE/MASQUE/QUIC/WebTransport).
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Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
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Design an A/B test — power analysis, randomization, and success metrics. Use when asked to "design an A/B test", "how many users do we need", or "run a power analysis".
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Provides chaos engineering best practices for resilience testing, fault injection, and game day planning. Use when designing resilience experiments, configuring chaos tools, planning game days, or when user mentions 'chaos engineering', 'resilience', 'litmus', 'game day', 'fault injection', 'chaos monkey', 'blast radius', 'steady state', 'failure mode'.
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Conjecture generation, sequence analysis, and experimental mathematics for mathematical discovery. Covers sequence analysis (OEIS lookups, recurrence relations, generating functions), pattern detection methods (finite differences, ratio analysis, modular patterns), conjecture generation workflow, classical integer sequences (Fibonacci, Catalan, partition numbers, Bernoulli numbers), combinatorial identities, the probabilistic method (Erdos, expected value arguments, Lovasz Local Lemma), AI-assisted discovery (FunSearch, Ramanujan Machine), and confidence calibration with cautionary tales (Mertens conjecture, Polya conjecture). Use when discovering patterns, analyzing sequences, generating conjectures, or working with combinatorial identities.
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Color theory principles for art education. Covers the three color properties (hue, saturation, value), color mixing systems (subtractive and additive), color relationships (complementary, analogous, triadic, split-complementary), color temperature, simultaneous contrast and the relativity of color perception, and practical palette construction. Use when analyzing color in artworks, planning color schemes, understanding optical phenomena in painting, or investigating Albers's Interaction of Color experiments.
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Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).
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This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
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Advises on setting up and validating topic models for survey and experimental text. Covers the discovery-versus-measurement question, choosing STM, LDA, or BERTopic, preprocessing consequences, prevalence and content formulas, topic-count selection across coherence, exclusivity and FREX, held-out likelihood, and residuals, validation of topics against human judgment, robustness, and DA-RT-compliant reporting. Use when the user has open-ended responses or another corpus and asks what topics are present, how many topics to use, about STM, searchK, coherence, or FREX, or wants topic prevalence compared across treatment arms or countries. Fixed-codebook coding goes to text-classification.
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Audits a methods section against a 45-item reporting checklist synthesized from the APSA Experimental Section rubric, JARS-Quant, CONSORT, and DA-RT, covering pre-registration, recruitment, randomization and treatments, sample flow and attrition, sample-size justification, three-tier results labeling, conjoint reporting, validity, and open-science infrastructure. Use when checking whether a methods section reports enough, preparing a submission or replication archive, asking what CONSORT, JARS, or DA-RT require, or documenting a deviation from a pre-analysis plan. Writing that plan before data collection goes to pre-registration-writing.
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